• DocumentCode
    2132181
  • Title

    Acoustic surveillance based on Higher-order Local Auto-Correlation

  • Author

    Sasou, Akira

  • Author_Institution
    Nat. Inst. of Adv. Ind. Sci. & Technol. (AIST), Japan
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The importance of video-surveillance applications has been increasing with the increase of crime and terrorism. In addition to traditional video cameras, the use of acoustic sensors in surveillance and monitoring applications is also becoming increasingly important. In this paper, we apply a High-order Local Auto-Correlation (HLAC) system, which has succeeded in video surveillance application, to extract features from acoustic signals for acoustic-surveillance systems. Experiment results confirmed that the proposed acoustic-surveillance system outperforms a cepstrum-based one under all SNR conditions.
  • Keywords
    acoustic signal processing; acoustic transducers; cepstral analysis; correlation methods; terrorism; video cameras; video surveillance; HLAC system; SNR conditions; acoustic sensors; acoustic signals; acoustic surveillance; acoustic-surveillance systems; cepstrum-based one; crime; high-order local auto-correlation system; higher-order local auto-correlation; monitoring applications; terrorism; video cameras; video-surveillance applications; Cepstrum; Feature extraction; Signal to noise ratio; Surveillance; Time frequency analysis; Vectors; Cepstrum; HLAC; acoustic surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing (MLSP), 2011 IEEE International Workshop on
  • Conference_Location
    Santander
  • ISSN
    1551-2541
  • Print_ISBN
    978-1-4577-1621-8
  • Electronic_ISBN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2011.6064587
  • Filename
    6064587